Apparatus for predicting future vendor performance

ABSTRACT

The present disclosure provides a vendor procurement apparatus for predicting future vendor performance for a new task based on previous vendor performance. The future vendor performance is determined by comparing the vendor&#39;s performance in related previously performed tasks to industry benchmarks in order to determine a rating for the previously performed tasks. These ratings are then weighted according to carrier specifications and averaged to create a prediction of vendor performance.

TECHNICAL FIELD

The present invention relates to the procurement of vendor services,more particularly, to a method and system for predicting futureperformance of a provider of legal professional services based onprevious performance of the provider.

BACKGROUND OF THE INVENTION

Carriers frequently need to employ vendors in areas across the countrythat are outside the carrier's normal area of operation. For example,insurance carriers often need to hire court reporters, adjusters, andattorneys across the United States to defend the insurance carriers inslip and fall cases, medical malpractice cases, car accident cases,worker's compensation cases, etc.

SUMMARY OF THE INVENTION

The selection of vendors by carriers can be a difficult task. Forexample, if an insurance carrier needs to hire a medical malpracticeattorney to represent it in a court in a faraway state, it can requirelarge amounts of time and money to locate attorneys that specialize inmedical malpractice, are located near the court, and are admitted topractice law in the faraway state. It can take even more time (1) togather data regarding the attorneys in order to determine whichattorneys meet specified criteria and (2) to evaluate which attorney tohire. For example, an insurance carrier may wish to select the attorneythat is the most effective and that has an average total cost less thana given amount. There is no guarantee that the subjective judgmentperformed by the insurance carrier will result in selecting the attorneybest suited to the insurance carriers' needs. This inefficient, ad hoc,and subjective decision making processes for vendor procurement andmanagement in, e.g., the insurance industry causes higher costs forpolicyholders.

A vendor selection tool is needed that allows carriers to efficientlyselect a vendor based on predefined criteria. The selection tool shouldalso allow the carrier to differentiate between vendors by weightingdifferent metrics applied to the vendors. Such a vendor selection toolprovides real world value by decreasing the time and money spent in theprocess of identifying and selecting vendor partners.

The present disclosure provides a vendor procurement apparatus forpredicting future vendor performance for a new task based on previousvendor performance. The prediction of future performance is determinedas a measure of a vendor's comparative performance to other vendors onsimilar tasks using weighted historical data.

According to one aspect of the disclosure, there is provided a vendorprocurement apparatus for predicting future vendor performance for a newtask based on previous vendor performance. The vendor procurementapparatus includes a non-transitory computer readable medium storing avendor database. The vendor database stores a list of vendor entriesregarding a group of vendors and at least one property for each vendorof the group of vendors. Each vendor entry identifies a particularvendor and objective data for at least one previous task performed bythe particular vendor. The objective data includes metrics regarding theparticular vendor's performance of the associated previous task. Thevendor procurement apparatus also includes a network interfaceconfigured to receive from a carrier a search request pertaining to thenew task and properties of a desired vendor. The vendor procurementapparatus further includes a processor configured to identify at leastone vendor in the vendor database. Each identified vendor has at leastone property that matches at least one property of the desired vendor.For each identified vendor, the processor is configured to identify atleast one matching previous task performed by the identified vendor thatmatches at least one characteristic of the new task, determine othermatching tasks in the vendor database that match at least onecharacteristic of the matching previous task performed by the identifiedvendor, and determine statistical properties of the metrics associatedwith the other matching tasks. For each identified at least one matchingprevious task performed by the identified vendor, the processor isconfigured to, for each metric associated with the identified matchingprevious task, convert the metric into a metric rating based on thedetermined statistical properties of that metric for the other matchingtasks and determine a task rating for the identified matching previoustask based on the at least one metric rating and a weighting factor. Theweighting factor applies a weight to each metric rating. The processoralso determines a prediction of future performance of the new task bythe identified vendor based on the determined at least one task rating.

Alternatively or additionally, the prediction of future performance fora given vendor is an average of the determined at least one task rating.

Alternatively or additionally, the determined statistical properties ofthe metrics associated with the other matching tasks include the meanvalue and the standard deviation of the metrics. The metric rating for agiven metric associated with the identified matching task is equal to aconstant value plus or minus a number of half standard deviations bywhich the given metric differs from the mean value of that metricassociated with the other matching tasks.

Alternatively or additionally, the metric rating is determined for eachmetric associated with the identified matching previous task and thetask rating is equal to the sum of each metric rating multiplied by theweight associated with the metric divided by the sum of the weightsassociated with each metric rating.

Alternatively or additionally, the constant value equals 5.

Alternatively or additionally, the weighting factor is received as partof the search request and/or is stored in a weighting factor databasestored in the non-transitory computer readable medium.

Alternatively or additionally, the carrier specifies the criteria fordetermining whether a particular property of a particular vendor matchesa particular property of the desired vendor and/or whether a particularprevious task stored in the vendor database matches the at least onecharacteristic of the new task.

Alternatively or additionally, the criteria for determining whether aparticular property of a particular vendor matches a particular propertyof the desired vendor and/or whether a particular previous task storedin the vendor database matches the at least one characteristic of thenew task is stored in a criteria matching database stored in thenon-transitory computer readable medium.

Alternatively or additionally, the other matching tasks do not includeprevious tasks performed by the identified vendor.

Alternatively or additionally, the new task is requested by an insurancecarrier and the vendors provide professional services.

Alternatively or additionally, the processor is further configured toanalyze the new task to determine the at least one characteristic of thenew task. The network interface is further configured to receive atleast one characteristic of the new task.

Alternatively or additionally, the network interface is furtherconfigured to provide to the carrier information regarding thedetermined prediction of future performance of the identified at leastone vendor.

Alternatively or additionally, the identified at least one vendorincludes multiple vendors. The information regarding the determinedprediction of future performance of the identified vendors is rankordered based on the prediction of future performance associated witheach vendor of the identified vendors.

According to another aspect of the disclosure, there is provided amethod for predicting future vendor performance for a new task based onprevious vendor performance. The method includes receiving from acarrier a search request pertaining to the new task and properties of adesired vendor and identifying at least one vendor in a vendor databasestored on a non-transitory computer readable medium. Each identifiedvendor has at least one property that matches at least one property ofthe desired vendor. For each identified vendor, the method identifyiesat least one matching previous task performed by the identified vendorthat matches at least one characteristic of the new task, determinesother matching tasks stored in the vendor database that match at leastone characteristic of the matching previous task performed by theidentified vendor, and determines statistical properties of metricsassociated with the other matching tasks. For each identified at leastone matching previous task performed by the identified vendor and foreach metric associated with the identified matching previous task, themethod converts the metric into a metric rating based on the determinedstatistical properties of that metric for the other matching tasks. Foreach identified at least one matching previous task, the method alsodetermines a task rating for the identified matching previous task basedon the at least one metric rating and a weighting factor. The weightingfactor applies a weight to each metric rating. The method alsodetermines a prediction of future performance of the new task by theidentified vendor based on the determined at least one task rating.

Alternatively or additionally, the prediction of future performance fora given vendor is an average of the determined at least one task rating.

Alternatively or additionally, the determined statistical properties ofthe metrics associated with the other matching tasks include the meanvalue and the standard deviation of the metrics. The metric rating for agiven metric associated with the identified matching task is equal to aconstant value plus or minus a number of half standard deviations bywhich the given metric differs from the mean value of that metricassociated with the other matching tasks.

Alternatively or additionally, the metric rating is determined for eachmetric associated with the identified matching previous task. The taskrating is equal to the sum of each metric rating multiplied by theweight associated with the metric divided by the sum of the weightsassociated with each metric rating.

According to an additional aspect of the disclosure, there is provided alegal professional service procurement apparatus for predicting futureperformance of a provider of professional services to insurance carriersfor a new task based on previous performance. The procurement apparatusincludes a non-transitory computer readable medium storing aprofessional service provider database. The professional serviceprovider database stores a list of provider entries regarding a group ofproviders of professional services to insurance carriers and at leastone property for each provider of the group of providers. Each providerentry identifies a particular provider and objective data for at leastone previous task performed by the particular provider. The objectivedata includes metrics regarding the particular provider's performance ofthe associated previous task. The procurement apparatus also includes anetwork interface configured to receive from an insurance carrier asearch request pertaining to the new task and properties of a desiredprovider. The procurement apparatus further includes a processorconfigured to identify at least one provider in the professional serviceprovider database, wherein each identified provider has at least oneproperty that matches at least one property of the desired provider. Foreach identified provider, the procurement apparatus identifies at leastone matching previous task performed by the identified provider thatmatches at least one characteristic of the new task, determines othermatching tasks in the professional service provider database that matchat least one characteristic of the matching previous task performed bythe identified vendor, and determines statistical properties of themetrics associated with the other matching tasks. For each identified atleast one matching previous task performed by the identified vendor, theprocurement apparatus is configured to, for each metric associated withthe identified matching previous task, convert the metric into a metricrating based on the determined statistical properties of that metric forthe other matching tasks and determine a task rating for the identifiedmatching previous task based on the at least one metric rating and aweighting factor. The weighting factor applies a weight to each metricrating. The procurement apparatus is also configured to determine aprediction of future performance of the new task by the identifiedprovider based on the determined at least one task rating.

Alternatively or additionally, the prediction of future performance fora given provider is an average of the determined at least one taskrating.

Alternatively or additionally, the determined statistical properties ofthe metrics associated with the other matching tasks include the meanvalue and the standard deviation of the metrics. The metric rating for agiven metric associated with the identified matching task is equal to aconstant value plus or minus a number of half standard deviations bywhich the given metric differs from the mean value of that metricassociated with the other matching tasks.

Alternatively or additionally, the metric rating is determined for eachmetric associated with the identified matching previous task. The taskrating is equal to the sum of each metric rating multiplied by theweight associated with the metric divided by the sum of the weightsassociated with each metric rating.

A number of features are described herein with respect to embodiments ofthis disclosure. Features described with respect to a given embodimentalso may be employed in connection with other embodiments.

For a better understanding of the present disclosure, together withother and further aspects thereof, reference is made to the followingdescription, taken in conjunction with the accompanying drawings. Thescope of the disclosure is set forth in the appended claims, which setforth in detail certain illustrative embodiments. These embodiments areindicative, however, of but a few of the various ways in which theprinciples of the disclosure may be employed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram representing the connections formed between avendor procurement apparatus, carrier system, and vendor system.

FIG. 2 is a block diagram of a vendor procurement system.

FIG. 3 is a block diagram of a search request.

FIG. 4 is a block diagram of a vendor database.

FIG. 5 is a ladder diagram representing transmission of informationbetween the vendor procurement apparatus, carrier system, and vendorsystem.

FIG. 6 is an exemplary user interface for a carrier to enter desiredvendor properties.

FIG. 7 is an exemplary user interface for modifying the weight appliedto a metric associated with previously performed tasks.

FIG. 8 is an exemplary user interface for displaying a list ofidentified vendors.

FIG. 9 is an exemplary vendor profile page for a vendor selected fromthe list of identified vendors in FIG. 8.

FIG. 10 is a flow diagram representing a method for predicting futurevendor performance for a new task based on previous vendor performance.

DETAILED DESCRIPTION OF THE INVENTION

The present invention is now described in detail with reference to thedrawings. In the drawings, each element with a reference number issimilar to other elements with the same reference number independent ofany letter designation following the reference number. In the text, areference number with a specific letter designation following thereference number refers to the specific element with the number andletter designation and a reference number without a specific letterdesignation refers to all elements with the same reference numberindependent of any letter designation following the reference number inthe drawings.

It should be appreciated that many of the elements discussed in thisspecification may be implemented in a hardware circuit(s), a processorexecuting software code or instructions which are encoded withincomputer readable media accessible to the processor, or a combination ofa hardware circuit(s) and a processor or control block of an integratedcircuit executing machine readable code encoded within a computerreadable media. As such, the term circuit, module, server, application,or other equivalent description of an element as used throughout thisspecification is, unless otherwise indicated, intended to encompass ahardware circuit (whether discrete elements or an integrated circuitblock), a processor or control block executing code encoded in acomputer readable media, or a combination of a hardware circuit(s) and aprocessor and/or control block executing such code.

The present disclosure provides a vendor procurement apparatus forpredicting future vendor performance for a new task based on previousvendor performance. The future vendor performance is determined bycomparing the vendor's performance in related previously performed tasksto industry benchmarks in order to determine a rating for the previouslyperformed tasks. These ratings are then weighted according to carrierspecifications and used to determine a prediction of vendor performance.

FIG. 1 depicts communication between carrier systems 12 a-c, a vendorprocurement apparatus 14, and vendor systems 16 a-c. When a carriersystem 12 requires the services of a vendor regarding a new task, thecarrier system 12 sends a search request to the vendor procurementapparatus 14 that pertains to the new task and includes properties of adesired vendor. Upon receiving the properties of the desired vendor, thevendor procurement apparatus 14 identifies vendors having propertiesmatching properties of the desired vendor. For each identified vendor,the vendor procurement apparatus 14 then determines a prediction offuture performance of the new task by the vendor. This prediction offuture performance is then transmitted by the vendor procurementapparatus 14 to the carrier system 12. The carrier system 12 thenselects a vendor system 16 to perform the new task. The selected vendormay be sent to the vendor procurement apparatus 14 and the vendorprocurement apparatus 14 may put the carrier system 12 in communicationwith the selected vendor 16.

Communication between the vendor procurement apparatus 14 and thecarrier systems 12 and vendor systems 16 is shown with solid lines.Communication between the carriers 12 and the vendors 16 is shown usingdashed lines. FIG. 1 only shows communication between a single carriersystem 12 a and the vendor systems 16 a-c in order to reduce clutter inthe figure and to make it easier to view the communication between thevendor procurement apparatus 14, the carriers 12, and the vendors 16.

Upon completion of the new task by the selected vendor 16, the selectedvendor 16 and/or the carrier system 12 report metrics regarding theperformance of the new task to the vendor procurement apparatus 14. Forexample, metrics may include the hours billed by the selected vendor,the outcome of the new task, the total cost of the new task, etc. Thisinformation is then stored by the vendor procurement apparatus 14.

In one embodiment, the carrier systems 12 are insurance carriers. Inthis embodiment, the vendors include providers of professional servicesto insurance carriers, e.g., court reporters, attorneys, independentadjusters, independent medical examiners, experts (accidentreconstruction, medical, engineer, etc.), etc.

Turning to FIG. 2, a vendor procurement system 10 is shown. The system10 includes at least one carrier system 12 (also referred to as a“carrier”), a vendor procurement apparatus 14, and at least one vendorsystem 16 (also referred to as a “vendor”). The financial messagingapparatus 14 receives a search request pertaining to a new task andproperties of a desired vendor from carrier systems 12 via a networkinterface 36. For example, the financial messaging apparatus 14 mayreceive from the carrier system 12 (1) a search request for a medicalmalpractice case in Las Vegas, Nev. and (2) properties of a desiredvendor specifying an attorney within 60 miles of Las Vegas, licensed topractice in Nevada, and having performed more than 50% of his/her workon medical malpractice cases. As will be described in greater detailbelow, in order to identify vendors matching the properties of thedesired vendor, a processor 30 of the vendor procurement apparatus 14analyzes vendor entries in a vendor database 34 stored in anon-transitory computer readable medium 32 of the vendor procurementapparatus 14. After identifying vendors matching the properties of thedesired vendor, the processor 30 determines a prediction of futureperformance of the new task by each identified vendor. The processor 30determines the prediction of future performance by comparing theperformance of the identified vendor in tasks similar to the new task(i.e., the task the search request is related to) with the performanceof other vendors in similar tasks. The prediction of future performanceof the new task by the identified vendors is then transmitted by thenetwork interface 36 of the vendor procurement apparatus 14 to thecarrier system 18 via the network 18.

The carrier system 12, vendor procurement apparatus 14, and vendorsystem 16 may be a computer system of one or more servers that eachinclude at least a processor 30, 50, 60, a network interface 36, 54, 74,and non-transitory computer readable medium 32, 52, 72. The computerreadable medium may include encoded thereon instructions for interfacingwith the corresponding network interface and reading and writing data tothe corresponding computer readable medium. The computer readable mediummay also include computer programs comprising instructions embodiedthereon that are executed by the corresponding processor.

Turning to FIG. 3, an exemplary search request 80 is shown. Theexemplary search request 80 includes the new task characteristics 82and/or the properties of the desired vendor 84. For example, the searchreport 80 may comprise a single data structure or separate but linkeddata structures. For example, the new task characteristics 82 anddesired vendor properties 84 may be included in a container that ensuresthe new task characteristics 82 and desired vendor properties 84 aretransmitted together by the carrier system 12. Alternatively, thedesired vendor properties 84 may be received as a separate file from thesearch request 80.

In another example, the search request 80 may contain only the desiredvendor properties 84. That is, the processor may analyze the new task todetermine the characteristic(s) of the new task. In this example, thenew task characteristics 82 may be determined based on the properties ofthe desired vendor 84. For example, in FIG. 3 the desired vendorproperties 84 specify that the carrier desires to locate an attorney (1)licensed to practice in Nevada, (2) located within 60 miles of LasVegas, (3) with at least 40% of his/her case work related to medicalmalpractice, (4) averages a total cost of less than $15,000, and (5) theaverage potential indemnity of cases handled by the attorney is greaterthan $150,000. In this example, the new task characteristics 82 may bedetermined by the processor 30 of the vendor procurement apparatus 14 tobe a (1) medical malpractice case (2) located in Las Vegas, Nev. and (3)having an indemnity risk of at least $150,000.

As is described in further detail below, the search request 80 mayadditionally include a weighting factor 86.

As will be understood by one of ordinary skill in the art, the searchrequest 80 may be sent in any suitable format. For example, the formatof the search request 80 may be a plain text document, spreadsheet, orproprietary format.

The search report 80 is not limited to information regarding a singlenew task, but may contain information regarding multiple new tasks. Forexample, a separate new task characteristic 82 and desired vendorproperty 84 may be contained in the search request 80 for each new task.In one example, the new tasks (for which information is contained in thesearch request 80) may all be related. For example, continuing theexemplary Las Vegas, Nev. medical malpractice case, the carrier system12 may send a single search request 80 requesting that the vendorprocurement apparatus 14 identify court reporters, attorneys, and expertwitnesses for use in the example case.

After the network interface 36 receives the search request 80 andproperties of the desired vendor 84, the processor 30 searches forvendors matching the desired vendor properties 84 using a vendordatabase 34 stored on the non-transitory computer readable medium 32.The vendor database stores a list of vendor entries regarding a group ofvendors and at least one property for each vendor of the group ofvendors. As shown in FIG. 4, each vendor entry identifies a particularvendor 90, properties of the vendor 92, and objective data 94 for atleast one previous task performed by the particular vendor. Theobjective data 94 includes metrics regarding the particular vendor'sperformance of the associated previous task.

The vendor properties may depend on the type of services rendered by thevendor. For example, the vendor properties 92 of a vendor that is anattorney may include location (i.e., address), states admitted topractice law, type of law practiced, percentage of cases in each type oflaw practiced, type of attorney (e.g., individual or firm), outcomes(e.g., amount of indemnity paid, awards or dismissals for mediation andtrials, etc.), wins (e.g., dismissal in a jury trial/arbitration),outcomes of trials in which the attorney was first chair, trainingmaterials provided by the attorney for the carriers (e.g., casestudies), list of clients and testimonials, assignment types (e.g.,Examination under oath, coverage opinions, defending a case), andspecialties (e.g., fraud, slip and fall, worker's compensation, etc.).In another example, the vendor properties 92 of a vendor that is anindependent adjuster may include address, cycle time (i.e., how long toclose case once received), and cost.

The metrics stored in the vendor database 34 may also differ dependingon the vendor type. For example, the previous task objective data 94 foran attorney may include metrics regarding case duration, legal fees,legal expenses, legal spend (sum of legal fees and legal expenses),indemnity, ratio of indemnity to legal spend, total cost (legal spendplus indemnity), budget accuracy, hours billed, and closed case review.Closed case review may be ratings supplied by the carrier that hired thevendor to perform the previous task. The closed case review may includeratings evaluating ethics, strategy (e.g., was the strategy consistentthroughout the case, was the strategy effective, etc.), communication(e.g., was communication prompt, did the vendor follow communicationguidelines specified by the carrier, etc.), and efficiency of staffing.In another example, the previous task objective data 94 for a courtreporter, independent adjuster, and/or expert may be limited to totalcost, carrier rating, closed case review, and hours billed.

As described above, the metrics stored in the vendor database 34 mayvary depending on the type of vendor. The vendor entry for a givenvendor may also not include each metric stored for other vendors of thesame type as the given vendor. For example, the vendor entry forattorney A may include four metrics, while the vendor entry for attorneyB may include 6 metrics.

As will be understood by one of ordinary skill in the art, the metricsstored in the vendor database 34 are not limited to those describedabove. The metrics may be adjusted to reflect any data useful to acarrier 12 or the vendor procurement apparatus 14 in order to select orpredict the performance of a vendor.

The processor 30 of the vendor procurement apparatus 14 identifies atleast one vendor in the vendor database 34 that has at least oneproperty that matches at least one property of the desired vendor. Inone example, the processor 30 may identify multiple vendors that matcheach of the properties of the desired vendor 84. In this example, theprocessor 30 does not identify any vendors that do not match all of theproperties of the desired vendor 84. That is, the processor 30 limitsthe identification of vendors to vendors that match all of theproperties of the desired vendor, because multiple vendors wereidentified without needing to lower the matching requirements toidentify vendors. In another example, however, the processor 30 may alsoidentify vendors that match a majority of the properties of the desiredvendor 84 (e.g., 75% or more). The number of properties of the desiredvendor 84 that a particular vendor must match to be identified may bedetermined based on the total number of identified vendors. For example,if only ten vendors match all of the desired vendor properties, theprocessor 30 may also identify all the vendors that match all but one ofthe desired vendor properties. If there are twenty additional vendorsthat match all but one of the desired vendor properties, then theprocessor 30 may stop identifying additional vendors. If, however, thereare only ten additional vendors that match all but one of the desiredvendor properties, then the processor 30 may also identify all of thevendors that match all but two of the desired vendor properties. In thisway, the processor 30 may ensure that a given number of vendors areidentified by decreasing the number of desired vendor properties 84 thata vendor must meet to be identified by the processor 30.

The carrier 12 may specify the criteria for determining whether aproperty of a vendor matches a particular property of the desiredvendor. For example, a desired vendor property 84 may be that the vendorspecializes in worker's comp cases. In this example, the carrier 12 mayprovide with the search request 80 the criteria for determining whethera vendor specializes in worker's comp cases. The carrier 12 may, e.g.,specify that an attorney that spends at least 40% of his/her timelitigating worker's comp cases qualifies as a specialist in worker'scomp cases.

In another example, the criteria for determining whether a property of agiven vendor matches a particular property of the desired vendor may bestored in a criteria matching database 40 stored in the non-transitorycomputer readable medium 32 of the vendor procurement apparatus 14. Inthis example, the carrier 12 may have previously supplied the criteriastored in the criteria matching database 40. Alternatively, the criteriastored in the criteria matching database 40 may be based on a defaultcriteria set by the vendor procurement apparatus 14 or a mixture of thedefault criteria and criteria supplier by the carrier 12. The defaultcriteria may be the default setting for each search request 80 suppliedby a carrier 12 unless the carrier 12 supplies an alternative criteria.

After the processor 30 identifies the vendor(s) matching the propertiesof the desired vendor, the processor 30 identifies at least one matchingprevious task performed by each identified vendor. A matching previoustask is (1) a task previously performed by a given identified vendor and(2) a task that matches at least one characteristic of the new task. Forexample, if vendor A is identified, then the processor 30 may identifyall tasks previously performed by vendor A that match all of thecharacteristics of the new task 82. In another example, the processor 30may identify the most recent tasks previously performed by vendor A thatmatch all of the characteristics of the new task 82. In still anotherexample, the processor 30 may identify those tasks previously performedby vendor A that match at least a majority (e.g., 50%, 75%, 85%, 95%,etc.) of the characteristics of the new task 82.

The processor 30 also determines other matching tasks in the vendordatabase 34 that match characteristic(s) of the matching previous taskperformed by the identified vendor. For example, if the processor 30locates a task performed by vendor A in 2010 that matches thecharacteristics of the new task, the processor 30 will also locate othertasks that match the characteristics of the 2010 task performed byvendor A. These other tasks that match the characteristics of the 2010task are then used to evaluate vendor A's performance in the 2010 task.In another embodiment, the processor 30 may instead determine othermatching tasks in the vendor database 34 that match thecharacteristic(s) of the new task. In both examples, the other matchingtasks may be limited to those previous tasks not performed by theidentified vendor.

By comparing the matching previous task performed by the identifiedvendor to other tasks similar to the matching previous task, a taskrating may be determined and stored for each previously performed taskwithout waiting for a search request regarding a new task. In this way,upon receiving a search request, the vendor procurement apparatus 14 maylocate matching previous tasks performed by the identified vendor anduse the already determined task ratings for the matching previous tasksto determine a prediction of future performance of the new task by anidentified vendor.

The carrier 12 may specify the criteria for determining whether aparticular previous task stored in the vendor database 34 matches thecharacteristic(s) of the new task. In another example, the criteria fordetermining whether a particular previous task stored in the vendordatabase 34 matches the characteristic(s) of the new task is stored in acriteria matching database 40 stored in the non-transitory computerreadable medium 32. The criteria may comprise a range of acceptablevalues for different possible characteristics of the new task. Forexample, assume a characteristic of the new task is a potentialindemnity of $150,000. The criteria may specify that previous tasksmatch the characteristic of potential indemnity of the new task, if thepotential indemnity of the previous task fell within the range of thepotential indemnity of the new task ±20%. Therefore, in this example,any previous task would match this characteristic if the potentialindemnity was within the range of $120,000 to $180,000. As will beunderstood by one of ordinary skill in the art, the criteria mayspecify, e.g., any suitable range of values or a specific value for eachcharacteristic of the new task.

Characteristics of the new task may include venue, potential indemnity,type of task (e.g., medical malpractice case, worker's comp case, etc.),budget, etc. As will be understood by one of ordinary skill in the art,characteristics of the new task are not limited to these examples, butmay include any characteristic that can be used to compare a new task topreviously performed tasks to determine if the two tasks are similar.

The processor 30 determines statistical properties of the metricsassociated with the other matching tasks. The determined statisticalproperties of the metrics associated with the other matching tasks mayinclude the mean value and the standard deviation of the metrics. Thedetermined statistical properties may also include other statisticalproperties of the metrics. As described in further detail below, thedetermined statistical properties are used to rate the identifiedvendor's previously performed tasks.

The processor 30 converts each metric associated with the identifiedmatching previous task performed by the identified vendor into a metricrating based on the determined statistical properties of the othermatching tasks. The metric rating for a given metric associated with theidentified matching task may be equal to a constant value plus or minusa number of half standard deviations by which the given metric differsfrom the mean value of that metric associated with the other matchingtasks. The metric rating may be determined for each metric associatedwith the identified matching previous task.

For example, Bob the attorney is identified as a vendor matching thecharacteristics of the desired vendor for a worker's compensation casein Reno, Nev. A worker's compensation assignment previously performed byBob is stored in the vendor database along with multiple metrics. Bob'srating for the completed assignment may be assessed by converting eachmetric for the completed assignment into a metric rating. If Bob's cycletime (i.e., one of the metrics) for the completed assignment is d₁, thend₁ is transformed into a metric rating r₁ by comparing d₁ to similartasks. For example, as described above, d₁ may be compared to othertasks identified in the vendor database that are similar to (i.e., matchthe characteristic(s) of) the worker's compensation assignment beingevaluated. In this example, r₁ is defined as variation from the mean ofthe other similar tasks. In one embodiment, r₁ is equal to a constantvalue (e.g., 5) ±the number of half standard deviations by which d₁differs from the mean of the cycle time (i.e., the metric) for the othersimilar tasks.

A task rating is determined for the identified matching previous taskbased on the metric rating(s) determined for the identified matchingprevious task and a weighting factor. The weighting factor applies aweight to each metric rating. In one example, the task rating may beequal to the sum of each metric rating for the identified matchingprevious task multiplied by the weight associated with the metricdivided by the sum of the weights associated with each metric rating.That is, where r₁, r₂, . . . , r_(x) are metric ratings for a givenprevious task and w₁, w₂, . . . , w_(x) are weighting factors for therespective metric ratings, the task rating R is determined using thefollowing equation:

$R = \frac{{r_{1}*w_{1}} + {r_{2}*w_{2}} + \ldots + {r_{x}*w_{x}}}{w_{1} + w_{2} + \ldots + w_{x}}$

The weighting factor may be received as part of the search requestand/or stored in a weighting factor database 38 stored in thenon-transitory computer readable medium 32 of the vendor procurementapparatus 14. For example, a default weighting factor may be stored inthe weighting factor database 38. This default weighting factor may beused unless or until a weighting factor is received from a vendor.

The weighting factor may include a set of individual weighting factors.The individual weighting factors may each be applied to a particularmetric. The weighting factor applied to determine a task rating may alsobe dependent upon the type (e.g., practice area) of the new task. Forexample, a carrier may create a weighting rule specific to worker'scompensation cases in Nevada. The weighting rule may specify thefollowing weights: Cycle Time 5/10, Legal Spend 4/10, Budget Accuracy2/10, Indemnity 7/10, Ratio Legal Spend/Indemnity 10/10. In thisexample, if the weighting factor does not include an individualweighting factor for a metric, the vendor procurement apparatus 14 mayapply the individual weighting factor for this metric stored in thedefault weighting factor or a common weighting factor to be used for anymetric for which a weighting factor is not specified.

The processor 30 determines a prediction of future performance of thenew task by the identified vendor based on the determined taskrating(s). In one example the prediction of future performance is equalto the determined task rating(s). Where multiple task ratings weredetermined for a given vendor, the prediction of future performance forthe given vendor may be an average of the determined task ratings. Aswill be understood by one of ordinary skill in the art, the predictionof future performance is not limited to being equal to a task rating orthe average of the determined task ratings for a given vendor. Theprediction of future performance may, e.g., be equal to determined taskrating(s) mapped to a single value based on predictive analysis. Forexample, if the vendor Bob has twenty-five task ratings in a range fromfour to eight, the processor 30 of the vendor procurement apparatus 14may analyze the distribution of Bob's task ratings to determine theprediction of future performance. For example, the oldest task ratingsmay be given a lower weight than task ratings for more recent tasks. Inanother example, it may be known that task ratings from a first courtare not good predictors of task performance in a second court. In thisexample, if the new task is for an assignment in the second court, thetask ratings associated with tasks performed in the first court may bediscarded or given a lower weight.

After the processor 30 determines the prediction of future performanceof the new task, the network interface 36 provides to the carrier 12information regarding the determined prediction of future performance ofthe identified vendor(s). The identified vendor need not be limited to asingle vendor. Rather, multiple vendors may be identified. When multiplevendors have been identified, the information regarding the determinedprediction of future performance of the identified vendors may be a rankordered list, in which the order of the identified vendors is based onthe prediction of future performance associated with each vendor of theidentified vendors. As will be understood by one of ordinary skill inthe art, the prediction of future performance is not limited to a rankordered list, but rather may take any form capable of conveying aprediction of how the identified vendor(s) will perform the new task.For example, the prediction of future performance may include a table ofvalues in which each identified vendor is associated with a numberindicating a prediction of future performance by the vendor.

In one embodiment, the vendor procurement apparatus 14 functions as alegal professional service procurement apparatus for predicting futureperformance of a provider of professional services to insurancecarriers. In this embodiment, the vendor database 18 may also bereferred to as a professional service provider database, in whichproviders correspond to vendors in the vendor database 18. Theprofessional service provider database stores a list of provider entriesregarding a group of providers of professional services to insurancecarriers and at least one property for each provider of the group ofproviders. The network interface 36 receives from an insurance carrier asearch request pertaining to the new task and properties of a desiredprovider. The processor 30 identifies at least one provider in theprofessional service provider database. Each identified provider has atleast one property that matches at least one property of the desiredprovider. For each identified provider, the processor 30 identifies atleast one matching previous task performed by the identified providerthat matches at least one characteristic of the new task. The processor30 also (1) determines other matching tasks in the professional serviceprovider database that match at least one characteristic of the matchingprevious task performed by the identified vendor and (2) determinesstatistical properties of the metrics associated with the other matchingtasks. For each identified at least one matching previous task performedby the identified vendor and each metric associated with the identifiedmatching previous task, the processor 30 converts the metric into ametric rating based on the determined statistical properties of thatmetric for the other matching tasks. The processor 30 also (1)determines a task rating for the identified matching previous task basedon the at least one metric rating and a weighting factor and (2)determines a prediction of future performance of the new task by theidentified provider based on the determined at least one task rating.

Turning to FIG. 5, a ladder diagram depicts the movement of informationbetween the carrier system 12, vendor procurement apparatus 14, andvendor system 18. The carrier system 12 transmits a search requestregarding a new task to the vendor procurement apparatus 14. Asdiscussed above regarding FIG. 3, the search request 80 may include newtask characteristics 82, desired vendor properties 84, and/or aweighting factor 86. The vendor procurement apparatus 14 analyzes thevendor database 34 to determine previous tasks performed by vendorsmatching the desired vendor properties 84.

After determining a prediction of future vendor performance for vendorsidentified as matching the desired vendor characteristic(s), the vendorprocurement apparatus 14 transfers the prediction of future vendorperformance to the carrier system 12. The carrier system 12 receives theprediction of future vendor performance and makes a selection regardingwhich vendor to enlist to perform the new task. The carrier system 12may select a particular vendor by displaying the prediction of futurevendor performance and allowing a user to choose a particular vendorbased on the predictions presented. Alternatively, the carrier system 12may automatically choose the vendor system 18 predicted to have the bestfuture performance. Upon selecting a particular vendor to enlist, thecarrier system 12 and vendor system 18 communicate to establish anagreement to perform the new task. The communication between the carriersystem 12 and the vendor system 18 may occur with or without involvementof the vendor procurement apparatus 14.

Following completion of the new assignment by the vendor system 18, thecarrier system 12 may provide a review of the vendor 18 to the vendorprocurement apparatus 14. The review may include a ranking of thevendor's performance in general on a scale (e.g., from one to fivestars). The review may also include separate rankings for differentaspects of the vendor (e.g., communication, strategy, etc.). This reviewmay then be used by the vendor procurement apparatus 14 to determine atask rating for the new task. This task rating of the new task may thenbe used by the vendor procurement apparatus 14 in the future whenpredicting a future performance of the vendor for new tasks.

As will be understood by one of ordinary skill in the art, informationmay be transmitted between the carrier system 12, vendor procurementapparatus 14, and vendor system 16 using any suitable protocol (e.g.,TCP/IP, Bluetooth, SMTP, HTTP, SSL, PPP, or IMAP).

Turning to FIG. 6, an exemplary user interface 120 for a carrier 12 toenter desired vendor properties 84 is shown. The user interface 120includes fields for inputting a list of venues worked (counties andstates), a location within a given distance from a particular location(e.g., San Francisco), assignment types, lines of business, vendor type,case types, and whether individuals or firms are searched.

With reference to FIG. 7, a user interface 125 for inputting a weightingfactor is shown. The user interface 125 includes slider bars forweighting the different metrics. The metrics include reviews, outcome,legal spend, cycle time, blended rate, hours bill/case, spend/indemnityratio, monthly spend/case, outcome in dollars, and budget accuracy. Byadjusting the position of the slider, a carrier 12 is able to adjust theweighting factor.

Turning to FIG. 8, after the vendor 12 enters the desired vendorproperties, the vendor 12 is presented a user interface 130 showing theidentified vendors. The user interface 130 in FIG. 8 does not include agraphical or numeric representation of the prediction of futureperformance of the new task by the identified vendors, but rather theidentified vendors are displayed in an order determined based on theprediction of future performance. That is, in FIG. 8, the first listedvendor 132 was determined to have a better prediction of futureperformance than second listed vendor 134 and the third listed vendor136. In another example, the prediction of future performance for eachvendor may be displayed along with the vendor properties shown in theuser interface 130. For example, the prediction of future performancemay be shown as a rating on a specified scale (e.g., from one to fivestars).

Turning to FIG. 9, a vendor profile 150 is shown. The vendor profile 150may be shown if a carrier 12 selects a vendor 16 from the list shown inFIG. 8. The vendor profile 150 allows the carrier 12 to view additionalinformation regarding the vendor 16.

Turning to FIG. 10, a method for predicting future vendor performancebased on previous vendor performance is shown. As described above, thesteps of the method may be performed by the processor 30 of the vendorprocurement apparatus 14. In processing block 162, a search requestpertaining to the new task and properties of a desired vendor arereceived. In process block 164, vendor(s) are identified in the vendordatabase that have properties that match properties of the desiredvendor. In process block 166, an identified vendor is selected. Inprocess block 168, previous task(s) performed by the identified vendorare identified that match characteristic(s) of the new task. In processblock 170, other matching tasks stored in the vendor database areidentified that match characteristic(s) of the matching previous taskperformed by the identified vendor. In process block 172, statisticalproperties of metrics associated with the other matching tasks aredetermined.

In processing block 174, an identified matching previous task performedby the identified vendor is selected. In process block 176, each metricassociated with the selected identified matching previous task isconverted into a metric rating based on the determined statisticalproperties of that metric for the other matching tasks. In process block178, a task rating is determined for the selected identified matchingprevious task based on the at least one metric rating and a weightingfactor. In decision block 180, a check is performed to determine ifthere are additional matching previous tasks performed by the identifiedvendor. If there are additional matching previous tasks, processingreturns to process block 174. If there are no additional matchingprevious tasks, processing continues to process block 182. In processblock 182, a prediction of future performance of the new task by theidentified vendor is determined based on the determined at least onetask rating.

In decision block 184, a check is performed to determine if there areadditional identified vendors for which a prediction of futureperformance has not yet been determined. If there are additionalidentified vendors to determine a prediction of future performance for,then processing returns to processing block 166 and a new identifiedvendor is selected. If there are no additional identified vendors todetermine a prediction of future performance for, then processing movesto processing block 186. In processing block 186, the prediction(s) offuture performance are transmitted to the carrier 12.

As will be understood by one of ordinary skill in the art, theprocessors 30 of the vendor procurement apparatus 14 may have variousimplementations including any suitable device, such as a programmablecircuit, integrated circuit, memory and I/O circuits, an applicationspecific integrated circuit, microcontroller, complex programmable logicdevice, other programmable circuits, or the like. The processor 30 mayalso include a non-transitory computer readable medium, such as randomaccess memory (RAM), a read-only memory (ROM), an erasable programmableread-only memory (EPROM or Flash memory), or any other suitable medium.Instructions for performing the methods described above may be stored inthe non-transitory computer readable medium and executed by theprocessor 30. The processor 30 may be communicatively coupled to thecomputer readable medium 32 and network interface 36 through a systembus, mother board, or using any other suitable structure known in theart.

The network interface 36 of the vendor procurement apparatus 14 may becommunicatively coupled to one or more carrier systems 12 and vendorsystems 16 via a network 18. The network 18 may be an open network, suchas the Internet, a private network, such as a virtual private network,or any other suitable network. The prediction of future performancetransmitted by the network interface 36 may comprise one or moreelectronic files including.

As will be understood by one of ordinary skill in the art, the networkinterface 36 may comprise a wireless network adaptor, an Ethernetnetwork card, or any suitable device for performing network basedcommunication between devices. The network interface 36 may becommunicatively coupled to the computer readable medium 32 such thateach network interface 36 is able to send data stored on the computerreadable medium 32 across the network 15 and store received data on thecomputer readable medium 32. The network interface 36 may also becommunicatively coupled to the processor 30 such that the processor 30is able to control operation of the network interface 36. The networkinterface 36, computer readable medium 32, and processor 30 may becommunicatively coupled through a system bus, mother board, or using anyother suitable manner as will be understood by one of ordinary skill inthe art.

Although the invention has been shown and described with respect tocertain exemplary embodiments, it is obvious that equivalents andmodifications will occur to others skilled in the art upon the readingand understanding of the specification. It is envisioned that afterreading and understanding the present invention those skilled in the artmay envision other processing states, events, and processing steps tofurther the objectives of system of the present invention. The presentinvention includes all such equivalents and modifications, and islimited only by the scope of the following claims.

What is claimed is:
 1. A vendor procurement apparatus for predictingfuture vendor performance for a new task based on previous vendorperformance, the vendor procurement apparatus comprising: anon-transitory computer readable medium storing: a vendor database,wherein: the vendor database stores a list of vendor entries regarding agroup of vendors and at least one property for each vendor of the groupof vendors; each vendor entry identifies a particular vendor andobjective data for at least one previous task performed by theparticular vendor; and the objective data includes metrics regarding theparticular vendor's performance of the associated previous task; anetwork interface configured to receive from a carrier a search requestpertaining to the new task and properties of a desired vendor; and aprocessor configured to: identify at least one vendor in the vendordatabase, wherein each identified vendor has at least one property thatmatches at least one property of the desired vendor; and for eachidentified vendor: identify at least one matching previous taskperformed by the identified vendor that matches at least onecharacteristic of the new task; determine other matching tasks in thevendor database that match at least one characteristic of the matchingprevious task performed by the identified vendor; determine statisticalproperties of the metrics associated with the other matching tasks; foreach identified at least one matching previous task performed by theidentified vendor: for each metric associated with the identifiedmatching previous task, convert the metric into a metric rating based onthe determined statistical properties of that metric for the othermatching tasks; and determine a task rating for the identified matchingprevious task based on the at least one metric rating and a weightingfactor, wherein the weighting factor applies a weight to each metricrating; and determine a prediction of future performance of the new taskby the identified vendor based on the determined at least one taskrating.
 2. The vendor procurement apparatus of claim 1, wherein theprediction of future performance for a given vendor is an average of thedetermined at least one task rating.
 3. The vendor procurement apparatusof claim 1, wherein: the determined statistical properties of themetrics associated with the other matching tasks include the mean valueand the standard deviation of the metrics; the metric rating for a givenmetric associated with the identified matching task is equal to aconstant value plus or minus a number of half standard deviations bywhich the given metric differs from the mean value of that metricassociated with the other matching tasks.
 4. The vendor procurementapparatus of claim 3, wherein: the metric rating is determined for eachmetric associated with the identified matching previous task; and thetask rating is equal to the sum of each metric rating multiplied by theweight associated with the metric divided by the sum of the weightsassociated with each metric rating.
 5. The vendor procurement apparatusof claim 3, wherein the constant value equals
 5. 6. The vendorprocurement apparatus of claim 1, wherein the weighting factor isreceived as part of the search request and/or is stored in a weightingfactor database stored in the non-transitory computer readable medium.7. The vendor procurement apparatus of claim 1, wherein the carrierspecifies the criteria for determining whether a particular property ofa particular vendor matches a particular property of the desired vendorand/or whether a particular previous task stored in the vendor databasematches the at least one characteristic of the new task.
 8. The vendorprocurement apparatus of claim 1, wherein the criteria for determiningwhether a particular property of a particular vendor matches aparticular property of the desired vendor and/or whether a particularprevious task stored in the vendor database matches the at least onecharacteristic of the new task is stored in a criteria matching databasestored in the non-transitory computer readable medium.
 9. The vendorprocurement apparatus of claim 1, wherein the other matching tasks donot include previous tasks performed by the identified vendor.
 10. Thevendor procurement apparatus of claim 1, wherein the new task isrequested by an insurance carrier and the vendors provide professionalservices.
 11. The vendor procurement apparatus of claim 1, wherein: theprocessor is further configured to analyze the new task to determine theat least one characteristic of the new task; or the network interface isfurther configured to receive at least one characteristic of the newtask.
 12. The vendor procurement apparatus of claim 1, wherein thenetwork interface is further configured to provide to the carrierinformation regarding the determined prediction of future performance ofthe identified at least one vendor.
 13. The vendor procurement apparatusof claim 1, wherein: the identified at least one vendor includesmultiple vendors; and the information regarding the determinedprediction of future performance of the identified vendors is rankordered based on the prediction of future performance associated witheach vendor of the identified vendors.
 14. A method for predictingfuture vendor performance for a new task based on previous vendorperformance, the method comprising: receiving from a carrier a searchrequest pertaining to the new task and properties of a desired vendor;identifying at least one vendor in a vendor database stored on anon-transitory computer readable medium, wherein each identified vendorhas at least one property that matches at least one property of thedesired vendor; for each identified vendor: identifying at least onematching previous task performed by the identified vendor that matchesat least one characteristic of the new task; determining other matchingtasks stored in the vendor database that match at least onecharacteristic of the matching previous task performed by the identifiedvendor; determining statistical properties of metrics associated withthe other matching tasks; for each identified at least one matchingprevious task performed by the identified vendor: for each metricassociated with the identified matching previous task, converting themetric into a metric rating based on the determined statisticalproperties of that metric for the other matching tasks; determining atask rating for the identified matching previous task based on the atleast one metric rating and a weighting factor, wherein the weightingfactor applies a weight to each metric rating; determining a predictionof future performance of the new task by the identified vendor based onthe determined at least one task rating.
 15. The method of claim 14,wherein the prediction of future performance for a given vendor is anaverage of the determined at least one task rating.
 16. The method ofclaim 14, wherein: the determined statistical properties of the metricsassociated with the other matching tasks include the mean value and thestandard deviation of the metrics; and the metric rating for a givenmetric associated with the identified matching task is equal to aconstant value plus or minus a number of half standard deviations bywhich the given metric differs from the mean value of that metricassociated with the other matching tasks.
 17. The method of claim 16,wherein: the metric rating is determined for each metric associated withthe identified matching previous task; the task rating is equal to thesum of each metric rating multiplied by the weight associated with themetric divided by the sum of the weights associated with each metricrating.
 18. A legal professional service procurement apparatus forpredicting future performance of a provider of professional services toinsurance carriers for a new task based on previous performance, theprocurement apparatus comprising: a non-transitory computer readablemedium storing: a professional service provider database, wherein: theprofessional service provider database stores a list of provider entriesregarding a group of providers of professional services to insurancecarriers and at least one property for each provider of the group ofproviders; each provider entry identifies a particular provider andobjective data for at least one previous task performed by theparticular provider; and the objective data includes metrics regardingthe particular provider's performance of the associated previous task; anetwork interface configured to receive from an insurance carrier asearch request pertaining to the new task and properties of a desiredprovider; and a processor configured to: identify at least one providerin the professional service provider database, wherein each identifiedprovider has at least one property that matches at least one property ofthe desired provider; and for each identified provider: identify atleast one matching previous task performed by the identified providerthat matches at least one characteristic of the new task; determineother matching tasks in the professional service provider database thatmatch at least one characteristic of the matching previous taskperformed by the identified vendor; determine statistical properties ofthe metrics associated with the other matching tasks; for eachidentified at least one matching previous task performed by theidentified vendor: for each metric associated with the identifiedmatching previous task, convert the metric into a metric rating based onthe determined statistical properties of that metric for the othermatching tasks; and determine a task rating for the identified matchingprevious task based on the at least one metric rating and a weightingfactor, wherein the weighting factor applies a weight to each metricrating; and determine a prediction of future performance of the new taskby the identified provider based on the determined at least one taskrating.
 19. The legal professional service procurement apparatus ofclaim 18, wherein the prediction of future performance for a givenprovider is an average of the determined at least one task rating. 20.The legal professional service procurement apparatus of claim 18,wherein: the determined statistical properties of the metrics associatedwith the other matching tasks include the mean value and the standarddeviation of the metrics; the metric rating for a given metricassociated with the identified matching task is equal to a constantvalue plus or minus a number of half standard deviations by which thegiven metric differs from the mean value of that metric associated withthe other matching tasks.
 21. The legal professional service procurementapparatus of claim 20, wherein: the metric rating is determined for eachmetric associated with the identified matching previous task; and thetask rating is equal to the sum of each metric rating multiplied by theweight associated with the metric divided by the sum of the weightsassociated with each metric rating.